This FastAPI web application leverages Open source LLMs (Large Language Model) using Ollama and LlamaIndex to build a RAG (Retrieval-Augmented Generation) framework using user notes as knowledge base. It provides endpoints for interacting with the knowledge base to get responses to user queries.

• FastAPI

• Ollama

• LlamaIndex

• Chat with LLM Endpoint: Use this endpoint to interact with Open Source LLM using Ollama by providing prompts and receiving responses.
  • Endpoint: http:https://localhost:8000/chat_with_llm?prompt=your_prompt_here
• Chat with Knowledge Base Endpoint: Use this endpoint to query the knowledge base built using LlamaIndex and retrieve relevant information.
  • Endpoint: http:https://localhost:8000/chat_with_knowledge_base?prompt=your_prompt_here

1. Clone the repository:

   git clone https://github.com/antoprince001/notes_scribe.git
   cd notes_scribe

2. Install dependencies:

   pip install -r requirements.txt

3. Add your notes file to the 'data/notes' directory

4. Run test suite:

   pytest

5. Run the FastAPI server:

   uvicorn main:app --reload

6. Open your web browser and navigate to the provided endpoints to interact with the REST API.